使用Python matplotlib库绘制漏斗图

pyecharts

pyecharts有漏斗图的模板(点击链接)，套用即可。

代码

from pyecharts import options as opts
from pyecharts.charts import Funneldata = [135043, 113413, 74909, 10366, 9018, 4151]
phase = ['总访客数量  ', '活跃访客数量', '注册用户数量', '预定用户数量', '支付用户数量', '复购用户数量']c = (Funnel().add("阶段", [list(z) for z in zip(phase, data)]).set_global_opts(title_opts=opts.TitleOpts(title="漏斗图")).render("funnel.html")
)

图片

虽然绘制方便，但是美观程度一般。

matplotlib

使用matplotlib绘制的思路是，绘制两个横向柱状图，其中一个设置成背景色遮住另一个的部分柱长，再绘制多边形填充两个柱子之间的间隔。

代码

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.patches import Polygon  # Polygon()可以用来传入按顺序组织的多边形顶点，从而生成出多边形
from matplotlib.collections import PatchCollectionplt.style.use('seaborn-dark')  # 设置主题
plt.rcParams['font.sans-serif'] = ['SimHei']  # 用来正常显示中文标签
plt.rcParams['axes.unicode_minus'] = False  # 用来正常显示负号visitor_num = 135043
data = [135043, 113413, 74909, 10366, 9018, 4151]
phase = ['总访客数量  ', '活跃访客数量', '注册用户数量', '预定用户数量', '支付用户数量', '复购用户数量']
data1 = [visitor_num/2 - i/2 for i in data]
data2 = [i+j for i,j in zip(data, data1)]
color_list = [ '#5c1d1d', '#892c2c','#994a4a', '#c56161', '#d48989', '#e2b0b0']  # 柱子颜色fig,ax = plt.subplots(figsize=(16, 9),facecolor='#f4f4f4')
ax.barh(phase[::-1], data2[::-1], color = color_list, height=0.7)  # 柱宽设置为0.7
ax.barh(phase[::-1], data1[::-1],  color = '#f4f4f4', height=0.7)  # 设置成背景同色
ax.axis('off')polygons = []
for i in range(len(data)):# 阶段ax.text(0,  # 坐标i,  # 高度phase[::-1][i],  # 文本color='black', alpha=0.8, size=16, ha="right")# 数量ax.text(data2[0] / 2 ,  i, str(data[::-1][i]) +'(' +str(round(data[::-1][i] / data[0] * 100, 1)) + '%)', color='black', alpha=0.8, size=18, ha="center")if i < 5:# 比例ax.text(data2[0] / 2 ,  4.4 - i, str(round(data[i+1] / data[i], 3) * 100) + '%', color='black', alpha=0.8, size=16, ha="center")# 绘制多边形polygons.append(Polygon(xy=np.array([(data1[i+1], 4+0.35-i),   # 因为柱状图的宽度设置成了0.7，所以一半便是0.35(data2[i+1], 4+0.35-i), (data2[i], 5-0.35-i), (data1[i], 5-0.35-i)])))# 使用add_collection与PatchCollection来向Axes上添加多边形
ax.add_collection(PatchCollection(polygons, facecolor='#e2b0b0',alpha=0.8));plt.show()

图片

ploty

2021-09-22更新
最近接触到ploty，发现有现成的库，较为美观，遂更新下文章，出处（https://plotly.com/python/funnel-charts/）。

基础漏斗图

import plotly.express as px
data = dict(number=[39, 27.4, 20.6, 11, 2],stage=["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"])
fig = px.funnel(data, x='number', y='stage')
fig.show()

堆积漏斗图

import plotly.express as px
import pandas as pd
stages = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"]
df_mtl = pd.DataFrame(dict(number=[39, 27.4, 20.6, 11, 3], stage=stages))
df_mtl['office'] = 'Montreal'
df_toronto = pd.DataFrame(dict(number=[52, 36, 18, 14, 5], stage=stages))
df_toronto['office'] = 'Toronto'
df = pd.concat([df_mtl, df_toronto], axis=0)
fig = px.funnel(df, x='number', y='stage', color='office')
fig.show()

带有各项指标的漏斗图

from plotly import graph_objects as gofig = go.Figure(go.Funnel(y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"],x = [39, 27.4, 20.6, 11, 2]))fig.show()

鼠标悬浮在图上可以看到当前阶段的各项占比

漏斗图自定义颜色

from plotly import graph_objects as gofig = go.Figure(go.Funnel(y = ["Website visit", "Downloads", "Potential customers", "Requested price", "Finalized"],x = [39, 27.4, 20.6, 11, 2],textposition = "inside",textinfo = "value+percent initial",opacity = 0.65, marker = {"color": ["deepskyblue", "lightsalmon", "tan", "teal", "silver"],"line": {"width": [4, 2, 2, 3, 1, 1], "color": ["wheat", "wheat", "blue", "wheat", "wheat"]}},connector = {"line": {"color": "royalblue", "dash": "dot", "width": 3}}))fig.show()

带有各项指标的堆积漏斗图

from plotly import graph_objects as gofig = go.Figure()fig.add_trace(go.Funnel(name = 'Montreal',y = ["Website visit", "Downloads", "Potential customers", "Requested price"],x = [120, 60, 30, 20],textinfo = "value+percent initial"))fig.add_trace(go.Funnel(name = 'Toronto',orientation = "h",y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent"],x = [100, 60, 40, 30, 20],textposition = "inside",textinfo = "value+percent previous"))fig.add_trace(go.Funnel(name = 'Vancouver',orientation = "h",y = ["Website visit", "Downloads", "Potential customers", "Requested price", "invoice sent", "Finalized"],x = [90, 70, 50, 30, 10, 5],textposition = "outside",textinfo = "value+percent total"))fig.show()

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